code: def test_zero_matches(self):
      # Test case where there's 0 matches
      references = [
          "The candidate has no alignment to any of the references".split()
      ]
      hypothesis = "John loves Mary".split()
  
      # Test BLEU to nth order of n-grams, where n is len(hypothesis).
      for n in range(1, len(hypothesis)):
          weights = (1.0 / n,) * n  # Uniform weights.
          assert sentence_bleu(references, hypothesis, weights) == 0
  
imports: import unittest
  import numpy
  from nltk.data import find
  from nltk.translate.bleu_score import SmoothingFunction, brevity_penalty, closest_ref_length, corpus_bleu, modified_precision, sentence_bleu
label_desc: Use image node_id 3 for calling the TestBLEU obj's underlying member method code with example usage: obj.test_zero_matches() without return types